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Ali Shebl
Researcher at University of Debrecen
Publications - 4
Citations - 60
Ali Shebl is an academic researcher from University of Debrecen. The author has contributed to research in topics: Support vector machine & Advanced Spaceborne Thermal Emission and Reflection Radiometer. The author has an hindex of 2, co-authored 4 publications receiving 7 citations. Previous affiliations of Ali Shebl include Tanta University.
Papers
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Multisource Data Analysis for Gold Potentiality Mapping of Atalla Area and Its Environs, Central Eastern Desert, Egypt
TL;DR: In this paper, airborne geophysical and remote sensing datasets were integrated for gold potentiality mapping (GPM) over the Atalla area in Central Eastern Desert, Egypt using the center for exploration targeting (CET) procedure.
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Reappraisal of DEMs, Radar and optical datasets in lineaments extraction with emphasis on the spatial context
Ali Shebl,Ali Shebl,Árpád Csámer +2 more
TL;DR: In this article, a lineament derivation environment through the integration of edge detection and line-linking algorithms is presented, where the authors show that the used optical sensors are less efficient than DEMs having the same spatial resolution.
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Stacked vector multi-source lithologic classification utilizing Machine Learning Algorithms: Data potentiality and dimensionality monitoring
Ali Shebl,Ali Shebl,Árpád Csámer +2 more
TL;DR: This study scrutinizes the efficacy of Artificial Neural Network, Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM) over hybrid datasets including optical, radar, DEMs and their derivatives and shows that SVM and MLC are much better than ANN.
Journal ArticleDOI
Lithological mapping enhancement by integrating Sentinel 2 and gamma-ray data utilizing support vector machine: A case study from Egypt
Ali Shebl,Ali Shebl,Mahmoud Abdellatif,Mahmoud Abdellatif,Musa Hissen,Mahmoud Abdelaziz,Mahmoud Abdelaziz,Árpád Csámer +7 more
TL;DR: In this article, the authors used Support Vector Machine (SVM) learning algorithm to classify combined high spectral resolution Sentinel 2 data with K, Th, and U content of the rocks to better differentiate a lithologically complex area in Egypt.